Increased vehicular queuing inside universities has amounted to pressing concerns for staff and students, distorting their time schedules to reach classes and office buildings on time. This paper attempts to alter the traditional transportation service behavior within university campuses to reduce traffic congestion and facilitate system effectiveness and reliability through a modeling-based routing and optimization approach. A qualitative conceptual model using a system thinking approach is used to identify the relationships and feedback between university shuttle system effectiveness, service performance, and traffic congestion. A bi-objective goal programming optimization model is developed and used to select the best alternative routes for university shuttle bus services during congested peak hours considering a continuous-circulation feeder mode. Qatar University shuttle bus service network is taken as the case for model implementation. A Monte Carlo simulation was used to ensure whether the daily bus capacity met the expected demand for each bus stop along the selected alternative routes. A sensitivity analysis was then conducted to identify the most sensitive bus stops along the best-selected routes. Results showed that the proposed alternative routes improved the system effectiveness by 75% and the alternative proposed routes satisfied the station’s daily demand.